A parallel neuro-controller for DC motors containing nonlinear friction

被引：66

作者：

Jang, JO ^{[1
]}

Jeon, GJ ^{[1
]}

机构：

[1] Kyungpook Natl Univ, Sch Elect & Elect Engn, Taegu 702701, South Korea

来源：

NEUROCOMPUTING | 2000年 / 30卷 / 1-4期

关键词：

friction compensation; neuro-controller; DC motor; tracking error bound;

D O I：

10.1016/S0925-2312(99)00128-9

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents an application of a parallel neuro-controller for compensating the effects induced by the friction in a DC motor system. A back-propagation neural network based on a gradient descent algorithm is employed, and a bound on the tracking error is derived from the analysis of the tracking error dynamics. The parallel neuro-controller is a combination of a linear controller and a neural network controller which compensates for nonlinear friction. The proposed scheme is implemented and tested on an IBM PC-based DC motor control system. The algorithm, simulations, and experimental results are described. The results are relevant for many precision drives, such as those found in industrial robots. (C) 2000 Elsevier Science B.V. All rights reserved.

引用

页码：233 / 248

页数：16

共 21 条

[1] A SURVEY OF MODELS, ANALYSIS TOOLS AND COMPENSATION METHODS FOR THE CONTROL OF MACHINES WITH FRICTION [J].